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Record W3128234252 · doi:10.3390/iecp2020-08796

Development and characterization of liposomal formulation containing phytosterols and tocopherols for reducing low-density lipoprotein cholesterol.

2020· article· en· W3128234252 on OpenAlexaffabout
Anas El‐Aneed, Asmita Poudel, George Gachumi, Zafer Dallal Bashi, Ildikó Badea

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCholesterol and Lipid Metabolism
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPhytosterolLiposomeBioavailabilityChemistrySonicationChromatographyCholesterolPhosphatidylcholineNutraceuticalFood scienceBiochemistryPharmacologyPhospholipidMembraneMedicine

Abstract

fetched live from OpenAlex

Purpose: Phytosterols are plant sterols with structural resemblance to cholesterol. United States Food and Drug Administration (FDA) and Health Canada have approved phytosterols as a cholesterol-lowering agent due to their ability to significantly reduce low-density lipoprotein cholesterol (LDL-C) in the range of 7-12%. However, phytosterols (lipophilic) have the potential to impart higher efficacy in the reduction of LDL-C if formulated in a delivery system that increases its bioavailability. In this work, we aim to develop and characterize a liposomal formulation containing phytosterols and tocopherols; the aim is to enhance cholesterol-lowering ability of phytosterols. We also aim to test the efficacy of brassicasterol (phytosterol unique to canola seeds) which has not yet been approved by the FDA. To prevent oxidation of phytosterols during formulation development and storage, tocopherols (vitamin E) are also added as antioxidants. Methods: Liposomes containing phytosterols and tocopherols were prepared using phosphatidylcholine as the lipid carrier and formulated using three different approaches -i) thin layer hydration homogenization, ii) thin layer hydration ultra-sonication, and iii) Mozafari method. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed and validated for quantifying liposomal phytosterols and tocopherols. Results: Liposomal vesicles prepared via homogenization and ultrasonication methods were significantly lower in size (<200 nm) in comparison to those produced by the Mozafari method (>200 nm). All three methods showed comparable zeta potential values (-9 to -14 mV), which is adequate for the physical stability of the vesicles. A new validated LC-MS/MS method with a total run time of seven minutes was applied to quantify four phytosterols (brassicasterol, campesterol, stigmasterol, and β-sitosterol) and three tocopherols (alpha, gamma, and delta) simultaneously. The run time of seven minutes is the shortest among reported methods to date. The liposomal formulation prepared by all three methods showed entrapment efficiency >89% for both phytosterols and tocopherols. Conclusion: Liposomes containing phytosterols and tocopherols were successfully developed and characterized with the aim of enhancing the efficacy of phytosterols. In vivo studies will be conducted using hamster animal model to compare the efficacy of liposomal phytosterols to marketed phytosterols containing products.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.253
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes2
Has abstractyes

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